Integrated Molecular Modeling and Machine Learning for Drug Design.

ABSTRACT: Modern therapeutic development often involves several stages that are interconnected, and multiple iterations are usually required to bring a new drug to the market. Computational approaches have increasingly become an indispensable part of helping reduce the time and cost of the research and development of new drugs. In this Perspective, we summarize our recent efforts on integrating molecular modeling and machine learning to develop computational tools for modulator design, including a pocket-guided rational design approach based on AlphaSpace to target protein-protein interactions, delta machine learning scoring functions for protein-ligand docking as well as virtual screening, and state-of-the-art deep learning models to predict calculated and experimental molecular properties based on

SUBMITTER: Xia S 

PROVIDER: S-EPMC10653122 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature